Instructions to use berng/myclass2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use berng/myclass2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="berng/myclass2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("berng/myclass2") model = AutoModelForImageClassification.from_pretrained("berng/myclass2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e40ed6ec4b45ef62025fc7cee4a165bdc7cb62f76c70fe04585d9ddd18c2c30
- Size of remote file:
- 5.37 kB
- SHA256:
- 0e502bbc84b4119d4657d551c18c9bb15a32c01cb943041afcaea9a8802de191
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